A featured contribution from Leadership Perspectives: a curated forum reserved for leaders nominated by our subscribers and vetted by the Education Technology Insights Europe Advisory Board.

Montclair State University

Building a Culture of Evidence-Based Improvement

Melissa Harris

Student Success Advocate

Balancing Accountability with Meaningful Assessment

The most important lesson I have learned in my role managing assessment and accreditation is the need to engage faculty, staff and school partners in all phases of the assessment process development, outcome sharing and discussion of resulting improvements. Creating and maintaining a balance between developing and using meaningful measures while meeting external compliance requirements is an ongoing challenge. Ensuring that the faculty and school partners, who have the closest ties to student learning and experiences, are empowered and have the opportunity to determine what and how student learning will be evaluated is key.

Curriculum is the faculty's purview, and the faculty need to design assessment strategies that align with the curriculum and P-12 schools’ needs and meet compliance requirements. If the assessment process is overly focused on accountability requirements, the opportunity to create meaningful learning experiences that lead to usable outcome measures can be lost. Faculty in the classroom and professionals in the schools bring that dose of reality and attention to what is most appropriate and meaningful for engaging students in learning. For these reasons, I try to stay out of the development process as much as possible and lend my expertise to ensure the experiences and assessments that faculty create meet accreditation and state requirements. By providing tools and clear expectations during development, faculty have the freedom to design assessments aligned with their instructional goals, effectively measure learning and meet accreditation requirements.

Turning Educational Data into Actionable Insight

In working with colleagues from other education program providers, I find a common challenge is having so much data from admissions, enrollment, retention, learning outcomes, financial aid and workforce outcomes- yet struggling to organize and analyze it all in a way that can inform decision-making. The abundance of available information can lead to feeling overwhelmed, being unable to identify the key metrics and difficulty determining where to begin organizing, summarizing and analyzing the most important data.

Additionally, the data is often messy, collected in multiple platforms and requires multiple steps to clean and compile into usable formats for analysis. Institutions often lack the time, resources and expertise needed to manage, analyze and share the data in appropriate and meaningful ways.

My advice is to keep assessment systems simple, with clearly defined goals and to start with a few key metrics. Collect only the data that will be used. Do not overcomplicate the process. Start by asking the questions you need answered. Then identify the data needed to answer the questions. Then share the answers with the faculty, staff, students and partners, allowing time and space to reflect upon the outcomes and discuss next steps.

The Next Evolution of Assessment and Accreditation

As Artificial Intelligence becomes increasingly prevalent in higher education, institutions are expected to transition toward automating reporting mechanisms and applying predictive modeling to enhance enrollment, retention and student success. However, institutions frequently lack the specialized resources or technical proficiency needed to deploy these models with efficacy. Although AI offers significant potential to facilitate these administrative operations, it is imperative that robust data security and governance frameworks be established within the institutions prior to implementation. The development of comprehensive policies and procedures is essential for institutions to build ethical, rigorous data structures that align with their mission and goals.

Aligning Data with Institutional Mission

While the concept of data-driven decision-making is frequently discussed in higher education, it can often amount to a catchphrase. Effective evidence-based practice requires a commitment to the institution's mission and objectives, ensuring that all strategic choices are fundamentally rooted in student learning, reducing the financial burden on students and enhancing student outcomes and the value of their education. Institutions should identify a concise set of key performance indicators that directly align with their core mission and goals. Sustained leadership engagement is essential, as is the provision of regular time and space where faculty, staff, students and community partners can critically examine and discuss assessment measures and outcomes.

The articles from these contributors are based on their personal expertise and viewpoints, and do not necessarily reflect the opinions of their employers or affiliated organizations.

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