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Online learning has changed higher education, emerging as a primary source for delivering courses and programs to students. As online learning has grown, more non-traditional students have entered college, many for the first time. Consequently, many of these non-traditional are experiencing online learning, and the technologies that deliver them, for the first time. Retention rates for online non-traditional students have been low and therefore understanding technology acceptance of these students is crucial to deploying online learning systems that help drive student success and retention. This quantitative research study developed and tested technology acceptance of online learning technologies using the technology acceptance model (TAM) with variables perceived ease of use (PEOU), perceived usefulness (PU), attitude (A), and intention to use (IU). The TAM variables were compared against the two dependent variables, traditional students (TS) and non-traditional students (NTS). Findings from 80 valid responses, 40 TS and 40 NTS, in an online survey and Mountain Empire Community College (MECC), showed that PEOU had a significant effect on PU, which is consistent with TAM. Findings showed that PEOU had no effect on (A) for TS but did have a significant effect on (A) for NTS. Further, PU had a significant effect on (A) and (A) had a significant effect on IU, which is consistent with TAM. Comparing TAM variables showed that there was a difference in technology acceptance between TS and NTS.

The massive open online course (MOOC) is a new approach for teaching online. MOOCs stand apart from traditional online classes in that they support thousands of learners through content and assessment mechanisms that can scale. A reason for their size is that MOOCs are free for anyone to take. Here we describe the design, development, and teaching of a MOOC called "Maps and the Geospatial Revolution." We explore the geography of the student population, the experience of teaching a MOOC, and evaluate its impacts on learning. We conclude with several key challenges and opportunities we see for MOOCs in geography.

A key challenge for mitigating poaching within protected areas is to understand the geospatial data that are collected by practitioners in protected areas and to characterize the ability to synthesize those data with landscape-level data to form a holistic picture of the movement patterns of humans and animals. Literature reviewed from the past 15 years on geospatial data collected by practitioners to mitigate wildlife poaching reveals a gap in our knowledge on how protected area practitioners make sense of geospatial data that are collected within protected areas. Geospatial data collected within protected areas provide an understanding of movement patterns of humans and animals, which can provide insight on best practices for poaching mitigation, to include where to emplace new geospatial sensors. We classify these data as device-based and human-generated, and their potential to provide geospatially referenced information that forms patterns of poaching activity. This article examines two primary types of geospatial data collected in protected areas, highlights the challenges associated with this data, and discusses knowledge gaps regarding how protected areas make sense of spatial data. We conclude with recommendations for future research on characterizing how geospatial data is represented in protected areas, and filling knowledge gaps on how protected area personnel use those data. [ABSTRACT FROM AUTHOR]

Frontiers in cartographic research are often found at the intersections where cartography overlaps with other domains in art, science, and technology. In this editorial, we summarize the major themes that are found in a new collection of invited literature reviews. Broad themes that emerge from this collection include the rise of novel virtual environments, ongoing user-centered design challenges for improving the utility and usability of geographic visualizations, and new approaches for representation and analysis for the development of geovisualizations. [ABSTRACT FROM AUTHOR]

Effective communication is a crucial component of patient-centered care and individuals with low health literacy face significant challenges in managing their health, leading to longer hospital stays and worse outcomes. Visual aids, such as medical illustrations and pictograms, can enhance patient understanding and memory retention; however, there is a lack in the medical field of tools for evaluating and improving a physician's ability to draw clinical illustrations for their patient. This article explores an aesthetic scale created in collaboration between Boston University Medical School and the Boston University Fine-Arts department. The scale scores basic design elements that could reasonably be improved in a clinical setting. A pilot study demonstrated interrater reliability between trained artists scoring images of varying concepts and visual quality with a Cronbach's alpha of 0.95. This scale has potential use in medical visual education and clinical evaluation. [ABSTRACT FROM AUTHOR]