Learning Engagement Assessment
Learning Engagement Assessment - Related Videos
13:57
Assessing the Multiple Dimensions of Engagement to Characterize Learning: A Neurophysiological Perspective
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Cited by 43 •
2015
This paper aims to describe the techniques involved in the collection and synchronization of the multiple dimensions (behavioral, affective and cognitive) of learners’ engagement during a task.
08:45
Assessing Cellular Target Engagement by SHP2 (PTPN11) Phosphatase Inhibitors
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Cited by 4 •
2020
The ability to assess target engagement by candidate inhibitors in intact cells is crucial for drug discovery. This protocol describes a 384 well format cellular thermal shift assay that reliably detects cellular target engagement of inhibitors targeting either wild-type SHP2 or its oncogenic variants.
10:07
Using Learning Outcome Measures to assess Doctoral Nursing Education
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Cited by 2 •
2010
The structure and process for measuring student learning outcomes through customizable assessment rubrics is discussed and applied to a doctoral nursing education program.
08:44
Assessing Spatial Learning and Memory in Small Squamate Reptiles
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Cited by 3 •
2017
This paper describes a modification of the Barnes maze, a standard rodent paradigm used to assess spatial memory and learning, for use in small squamate reptiles.
14:02
Measuring Engagement of Spectators of Social Digital Games
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2021
We propose a methodology that enables measuring engagement of spectators in a social digital game combining physiological and self-reported data. As this digital game involves a group of freely moving people, the experience is filmed using a synchronizing technique that links physiological data with events in the game.
FAQs
Combining these sources reduces the risk of interpreting engagement through one narrow signal. Observations can show participation and interaction, questionnaires capture learners’ responses, and performance data or digital records provide additional evidence of persistence and progress. Taken together, these indicators help educators judge whether instruction supports meaningful involvement rather than merely visible activity.
Meaningful engagement is better examined by relating what learners do to how they respond and perform. Participation and attention provide behavioral evidence, while responses to activities and performance data indicate whether involvement is connected with progress or conceptual understanding. This comparison helps instructors avoid treating visible participation or isolated interaction as sufficient evidence of learning.
In engineering education, engagement patterns can expose barriers that are difficult to see from academic outcomes alone. Evidence from laboratory or design-based instruction may show whether learners are collaborating, persisting with problems, and responding to activities. Instructors can then adapt course design or teaching to strengthen problem-solving and conceptual understanding.
A practical cycle begins by selecting indicators relevant to the learning experience, such as interaction, persistence, attention, or responses to activities. Instructors then gather evidence through suitable sources, review it consistently alongside performance information, and use the findings to adjust instruction. Repeating this cycle supports course improvement rather than a one-time judgment.
Digital learning records are useful when instructors need evidence across learning activities rather than relying only on direct observation. Examining these records alongside questionnaires, observations, and performance data can connect patterns of participation or persistence with academic outcomes. Their main value is comparative: consistent records help reveal changes in engagement and indicate where instructional adjustments may be needed.
Laboratory and design-based courses provide particularly relevant settings for this assessment because learning depends on more than final answers. Instructors can examine interaction, persistence, responses to activities, and performance to evaluate how course design supports collaboration, problem-solving, and conceptual understanding. The findings can guide changes that make these experiences more supportive of learner progress.