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Description
Multimodal presentations have been found to facilitate learning, however, may be a disadvantage for low spatial ability students if they require spatial visualization. This disadvantage stems from their limited capacity to spatially visualize and retain information from both text and diagrams for integration. Similarly, working memory capacity (WMC) likely plays

Multimodal presentations have been found to facilitate learning, however, may be a disadvantage for low spatial ability students if they require spatial visualization. This disadvantage stems from their limited capacity to spatially visualize and retain information from both text and diagrams for integration. Similarly, working memory capacity (WMC) likely plays a key role in a learner's ability to retain information presented to them via both modalities. The present study investigated whether or not the act of self-explaining helps resolve deficits in learning caused by individual differences in spatial ability, working memory capacity, and prior knowledge when learning with text, or text and diagrams. No interactions were found, but prior knowledge consistently predicted performance on like posttests. The author presents methodological and theoretical explanations as to the null results of the present study.
ContributorsGutierrez, Pedro J (Author) / Craig, Scotty D. (Thesis advisor) / Branaghan, Russell (Committee member) / Sanchez, Cristopher (Committee member) / Arizona State University (Publisher)
Created2014
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Description
The current study investigated the task of coloring static images with multimedia learning to determine the impact on retention and transfer scores. After watching a multimedia video on the formation of lightning participants were assigned to either a passive, active, or constructive condition based on the ICAP Framework. Participants colored

The current study investigated the task of coloring static images with multimedia learning to determine the impact on retention and transfer scores. After watching a multimedia video on the formation of lightning participants were assigned to either a passive, active, or constructive condition based on the ICAP Framework. Participants colored static images on key concepts from the video, passive condition observed the images, active condition colored the images by applying the concepts, and the constructive condition colored the images by generating new ideas and concepts. The study did not support the hypothesis that the constructive condition would have increased retention and transfer scores over the active and passive conditions. The mental effort measures did not show significance among groups in relation to learning but perception measures did show an increase in participants enjoyment and engagement. Since the coloring craze has become more accepted for adults then could coloring be a way to increase participants learning through engagement.
ContributorsWilliams, Jennifer S (Author) / Craig, Scotty D. (Thesis advisor) / Roscoe, Rod (Committee member) / Branaghan, Russell (Committee member) / Arizona State University (Publisher)
Created2018
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Description
This study investigated the ability to relate a test taker’s non-verbal cues during online assessments to probable cheating incidents. Specifically, this study focused on the role of time delay, head pose and affective state for detection of cheating incidences in a lab-based online testing session. The analysis of a test

This study investigated the ability to relate a test taker’s non-verbal cues during online assessments to probable cheating incidents. Specifically, this study focused on the role of time delay, head pose and affective state for detection of cheating incidences in a lab-based online testing session. The analysis of a test taker’s non-verbal cues indicated that time delay, the variation of a student’s head pose relative to the computer screen and confusion had significantly statistical relation to cheating behaviors. Additionally, time delay, head pose relative to the computer screen, confusion, and the interaction term of confusion and time delay were predictors in a support vector machine of cheating prediction with an average accuracy of 70.7%. The current algorithm could automatically flag suspicious student behavior for proctors in large scale online courses during remotely administered exams.
ContributorsChuang, Chia-Yuan (Author) / Femiani, John C. (Thesis advisor) / Craig, Scotty D. (Thesis advisor) / Bekki, Jennifer (Committee member) / Arizona State University (Publisher)
Created2015