E-learning Pilot Testing
E-learning Pilot Testing - Related Videos
07:17
Pilot Testing
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2023
Source: Laboratories of Gary Lewandowski, Dave Strohmetz, and Natalie Ciarocco—Monmouth University In any experiment researchers have the challenge of creating experiences for participants that are consistent (i.e., reliable) and authentic (i.e., valid). Yet there are many ways to manipulate any one variable. For example, if you want participants to feel sad, you can have them think of their own sad memory, watch a sad video, or read a sad story. Researchers must find the best way to...
08:52
Novel Object Recognition Test for the Investigation of Learning and Memory in Mice
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Cited by 797 •
2017
The object recognition test (ORT) is a simple and efficient assay for evaluating learning and memory in mice. The methodology is described below.
06:34
Operation of a 25 KWth Calcium Looping Pilot-plant with High Oxygen Concentrations in the Calciner
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Cited by 7 •
2017
This manuscript describes a procedure for operating a calcium looping pilot-plant for post-combustion carbon capture with high oxygen concentrations in the calciner in order to reduce or eliminate the flue gas recycle.
01:21
Pilot and Numeric Relaying
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2024
Pilot relaying is a type of differential protection used in power systems. It compares electrical quantities at the terminals of equipment via a communication channel instead of direct relay interconnection. This method is essential for transmission lines where the terminals are far apart, typically up to 80 km for lines with 69 to 115 kV ratings. Four types of communication channels are used for pilot relaying: Pilot Wires: These are separate electrical circuits operating at DC, 50 to 60 Hz,...
09:14
Low-stress Route Learning Using the Lashley III Maze in Mice
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Cited by 25 •
2010
The Lashley III maze is a route-learning task that does not rely on aversive stimuli or visual cues. It is thus a highly attractive option for evaluating learning and memory, especially in aging mice or otherwise where stress is a consideration.
FAQs
Participants should represent the learners who will eventually use the medical course, such as students or healthcare professionals. Their experience with digital learning, familiarity with the subject, and likely learning needs can influence the feedback they provide. A representative group helps developers detect barriers that might otherwise remain hidden until the course reaches a larger population.
Reviewers should examine instructional content, navigation, technical performance, accessibility, workload, and learning activities. These areas reveal different problems: explanations may be confusing, course movement may be difficult, delivery may fail technically, or activities may place unsuitable demands on learners. Examining the features together shows whether the course functions as a coherent educational experience.
Pilot findings support an iterative refinement process rather than a single final review. Developers can use identified problems to revise unclear explanations, remove usability barriers, and address delivery issues before broader implementation. Repeating this improvement cycle strengthens alignment with learners’ needs and reduces the risk that preventable course weaknesses will affect many users.
A typical workflow begins by selecting representative users and assigning selected course modules. Participants then complete those modules while reviewers examine the learning experience and technical delivery. Feedback is collected through surveys, interviews, or performance data, after which developers identify problems and refine the course. This sequence connects direct user experience with targeted course improvement.
Surveys can gather structured feedback from participants, while interviews allow reviewers to explore learners’ experiences and clarify specific concerns. Performance data adds evidence from how participants perform during the learning activities. Used together, these sources help distinguish perceived difficulties from observed problems and provide a broader basis for revising medical instruction.
It is especially valuable before a digital course is introduced to a larger population of medical students or healthcare professionals. Testing at this stage can expose confusing content, accessibility or navigation barriers, technical delivery problems, and unsuitable workload. Addressing these findings beforehand supports educational quality and reduces implementation risks across the intended medical learning setting.