While program- and institution-level learning assessment in higher education has received substantial attention, much less emphasis has been placed on the assessment of learning in noncredit continuing education in higher education institutions. Learning assessment is sparse in this area because these learning experiences may be shorter in…

Learning outcomes and assessment frameworks guide educators in curricular decisionmaking, impact assessment, gap identification, and equity evaluation, aligning with anticipated learning objectives. Common frameworks include Bloom's taxonomy, Kirkpatrick's model, Fink's taxonomy, and Moore's Outcomes model. The authors identified a lack of focus…

Artificial intelligence is a tool that has expanded exponentially since it became available to the public. It will disrupt industry and higher education. While many faculty have concerns about the impact of AI, professional staff members are using AI at a higher rate than their faculty peers. In specific administrative areas, the use of AI will…

The current research utilized a modern word cloud tool to assess the effectiveness of course objectives and outcomes of a community-engaged learning and core curriculum course at a private Catholic University. The foundational course revolves around social justice using the setting of sport and physical activity. Beginning with a final reflection…

Meaningfully engaging faculty in assessment presents a continual challenge for general education administrators. Faculty perceptions of assessment--including that assessment serves no purpose other than "checking a box" for accreditation and that it conveys little benefit to the instructor--often hinder instructor engagement. A low-cost…

Colleges and universities depend upon external approvals from accreditors, government agencies, and national organizations. These approvals require periodic review of institution-prepared reports and self-studies documenting the continued validity of offered degrees and programs, student support and success, institutional effectiveness, and…

Recent advancements in generative artificial intelligence (AI) have disrupted assessment practices within the higher education sector. The efficacy of existing assessment approaches is under reexamination with the introduction of generative AI's ability to generate human-like text. Simultaneously, there are calls to integrate generative AI into…

High quality student outcome measures provide the foundation for effective learning assessment. These outcomes can be organized into different categories, such as skills or habits of mind, and evidence types, such as direct or indirect. Prevailing models of assessment, however, focus only on the distinction between direct and indirect evidence…

The primary aim of institutional learning outcomes assessment is the creation of a culture of assessment where faculty use evidence-based data to validate and improve teaching and learning for the benefit of students. Faculty are key to these processes and yet, they are often woefully disengaged from them. This paper presents findings from an…

In the ever-evolving domain of higher education, the introduction of artificial intelligence (AI) marks a pivotal moment, promising to redefine the essence of academic assessment. This evolution brings with it a surge of potential to streamline and enrich assessment methodologies, yet it simultaneously ushers in a period of uncertainty and…