The Experiential Learning Design Accelerator

This chapter will describe the Experiential Learning Design Accelerator (the Accelerator) initiative at the University of Arizona and its impact on this campus. Specifically, this chapter will address the campus-wide faculty selection process, programmatic components of the Accelerator including topical workshops exploring themes such as reciprocity within community partnerships, iterative development embedded in student-facing assignments, and the design and execution of effective digital learning tools. Critically, this chapter will look at the foundational training in design thinking to inform course design and delivery.

Integrating ALN into an Independent Study Distance Education Program: NVCC Case Studies

This paper describes eight ALN courses developed under various Sloan Foundation-funded degree program initiatives at Northern Virginia Community College (NVCC) Extended Learning Institute (ELI). These chemistry, engineering, mathematics, and information technology courses offer useful lessons about what makes ALN courses successful. The courses incorporated ALN into an independent study format to increase interaction among learning participants while maximizing learner convenience and flexibility; some courses also focused on both online and in-person collaboration. A wide variety of other course design and delivery strategies contributed to the courses' success. The results of this study indicate that ALN courses can be viable and successful for community college students and that ALN can succeed in a distance education program delivered in an independent study format to motivated learners. NVCC/ELI's experience also suggests that ALN works within a multiple media approach to course design and delivery; that faculty selection, support, and development are critical factors in assuring quality ALN courses; that a wide variety of best practices can result in successful ALN courses; and that the learning effectiveness of ALN courses will continue to improve as better tools, content, and support are developed.

Factors Associated With Successful Research Departments

Background and Objectives: Inadequate resources have led to family medicine research divisions at varying stages of development. The purpose of this analysis was to identify the factors that family medicine research “bright spot” departments perceive to be crucial to their success. Methods: In this qualitative analysis, we identified bright spot dimensions and used a snowball sampling approach to identify medical school-based departments considered to be research bright spots. With 16 leaders from eight departments, we conducted semistructured interviews, covering historical events, leadership, partnerships, mentors, faculty selection, and training. We recorded and transcribed interviews and used a template-driven approach to data analysis, iteratively defining and modifying codes. At least two reviewers independently coded each interview, and coding discrepancies were discussed until consensus was reached. Results: We identified the following themes: (1) Leadership was committed to research; (2) Research was built around teams of researchers; (3) Interdisciplinary teams facilitated by partnerships allowed the department to tackle complex problems; (4) The convergence of researchers and clinicians ensured that the research was relevant to family medicine; (5) Departments had cultures that engendered trust, leading to effective collaboration; (6) These teams were composed of intrinsically motivated individuals supported by mentorship and resources; (7) When deciding which questions to pursue, departments balanced the question’s alignment with the individual researcher’s passion, relevance to family medicine, and fundability. Conclusions: A commitment to research from an engaged chair, partnerships, integrating front-line clinicians, and supporting intrinsically motivated individuals were important for bright spots. Applying these concepts may be an important strategy for generating knowledge.

A Neutrosophic Multi-Criteria Decision Making Method

This work presents a method of multi-criteria decision making (MCDM) using neutrosophic sets. Besides studying some interesting mathematical properties of the method, algorithm viz neut-MCDM is presented. The work also furnishes the fundamentals of neutrosophic set theory succinctly, to provide a first introduction of neutrosophic sets for the MCDM community. To illustrate the computational details, neut-MCDM has been applied to the problem of university faculty selection against a given set of criteria.