Matching Items (44)
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 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
Description
Undeclared undergraduates participated in an experimental study designed to explore the impact of an Internet-delivered "growth mindset" training on indicators of women's engagement in science, engineering, technology, and mathematics ("STEM") disciplines. This intervention was hypothesized to increase STEM self-efficacy and intentions to pursue STEM by strengthening beliefs in intelligence as malleable ("IQ attitude") and discrediting gender-math stereotypes (strengthening "stereotype disbelief"). Hypothesized relationships between these outcome variables were specified in a path model. The intervention was also hypothesized to bolster academic achievement. Participants consisted of 298 women and 191 men, the majority of whom were self-identified as White (62%) and 18 years old (85%) at the time of the study. Comparison group participants received training on persuasive writing styles and control group participants received no training. Participants were randomly assigned to treatment, comparison, or control groups. At posttest, treatment group scores on measures of IQ attitude, stereotype disbelief, and academic achievement were highest; the effects of group condition on these three outcomes were statistically significant as assessed by analysis of variance. Results of pairwise comparisons indicated that treatment group IQ attitude scores were significantly higher than the average IQ attitude scores of both comparison and control groups. Treatment group scores on stereotype disbelief were significantly higher than those of the comparison group but not those of the control group. GPAs of treatment group participants were significantly higher than those of control group participants but not those of comparison group participants. The effects of group condition on STEM self-efficacy or intentions to pursue STEM were not significant. Results of path analysis indicated that the hypothesized model of the relationships between variables fit to an acceptable degree. However, a model with gender-specific paths from IQ attitude and stereotype disbelief to STEM self-efficacy was found to be superior to the hypothesized model. IQ attitude and stereotype disbelief were positively related; IQ attitude was positively related to men's STEM self-efficacy; stereotype disbelief was positively related to women's STEM self-efficacy, and STEM self-efficacy was positively related to intentions to pursue STEM. Implications and study limitations are discussed, and directions for future research are proposed.
ContributorsFabert, Natalie Shay (Author) / Bernstein, Bianca L. (Thesis advisor) / Kinnier, Richard (Committee member) / Dawes, Mary (Committee member) / Bekki, Jennifer (Committee member) / Arizona State University (Publisher)
Created2014
Description
Observational tutoring has been found to be an effective method for teaching a variety of subjects by reusing dialogue from previous successful tutoring sessions. While it has been shown content can be learned through observational tutoring it has yet to been examined if a secondary behavior such as goal-setting can be influenced. The present study investigated if observing virtual humans engaging in a tutoring session on rotational kinematics with embedded positive goal oriented dialogue would increase knowledge of the material and perpetuate a shift an observer's goal-orientation from performance avoidance goal orientation (PAVGO) to learning goal orientation (LGO). Learning gains were observed in pre to post test knowledge retention tests. Significant changes from pretest to posttest occurred across conditions for LGO. Additionally, significant changes from PAVGO pretest to posttest were observed in the control condition however PAVGO did not significantly change in the experimental condition.
ContributorsTwyford, Jessica (Author) / Craig, Scotty D. (Thesis advisor) / Niemczyk, Mary (Committee member) / Kuzel, Michael (Committee member) / Arizona State University (Publisher)
Created2014
Description
Technological advances have enabled the generation and collection of various data from complex systems, thus, creating ample opportunity to integrate knowledge in many decision making applications. This dissertation introduces holistic learning as the integration of a comprehensive set of relationships that are used towards the learning objective. The holistic view of the problem allows for richer learning from data and, thereby, improves decision making.
The first topic of this dissertation is the prediction of several target attributes using a common set of predictor attributes. In a holistic learning approach, the relationships between target attributes are embedded into the learning algorithm created in this dissertation. Specifically, a novel tree based ensemble that leverages the relationships between target attributes towards constructing a diverse, yet strong, model is proposed. The method is justified through its connection to existing methods and experimental evaluations on synthetic and real data.
The second topic pertains to monitoring complex systems that are modeled as networks. Such systems present a rich set of attributes and relationships for which holistic learning is important. In social networks, for example, in addition to friendship ties, various attributes concerning the users' gender, age, topic of messages, time of messages, etc. are collected. A restricted form of monitoring fails to take the relationships of multiple attributes into account, whereas the holistic view embeds such relationships in the monitoring methods. The focus is on the difficult task to detect a change that might only impact a small subset of the network and only occur in a sub-region of the high-dimensional space of the network attributes. One contribution is a monitoring algorithm based on a network statistical model. Another contribution is a transactional model that transforms the task into an expedient structure for machine learning, along with a generalizable algorithm to monitor the attributed network. A learning step in this algorithm adapts to changes that may only be local to sub-regions (with a broader potential for other learning tasks). Diagnostic tools to interpret the change are provided. This robust, generalizable, holistic monitoring method is elaborated on synthetic and real networks.
The first topic of this dissertation is the prediction of several target attributes using a common set of predictor attributes. In a holistic learning approach, the relationships between target attributes are embedded into the learning algorithm created in this dissertation. Specifically, a novel tree based ensemble that leverages the relationships between target attributes towards constructing a diverse, yet strong, model is proposed. The method is justified through its connection to existing methods and experimental evaluations on synthetic and real data.
The second topic pertains to monitoring complex systems that are modeled as networks. Such systems present a rich set of attributes and relationships for which holistic learning is important. In social networks, for example, in addition to friendship ties, various attributes concerning the users' gender, age, topic of messages, time of messages, etc. are collected. A restricted form of monitoring fails to take the relationships of multiple attributes into account, whereas the holistic view embeds such relationships in the monitoring methods. The focus is on the difficult task to detect a change that might only impact a small subset of the network and only occur in a sub-region of the high-dimensional space of the network attributes. One contribution is a monitoring algorithm based on a network statistical model. Another contribution is a transactional model that transforms the task into an expedient structure for machine learning, along with a generalizable algorithm to monitor the attributed network. A learning step in this algorithm adapts to changes that may only be local to sub-regions (with a broader potential for other learning tasks). Diagnostic tools to interpret the change are provided. This robust, generalizable, holistic monitoring method is elaborated on synthetic and real networks.
ContributorsAzarnoush, Bahareh (Author) / Runger, George C. (Thesis advisor) / Bekki, Jennifer (Thesis advisor) / Pan, Rong (Committee member) / Saghafian, Soroush (Committee member) / Arizona State University (Publisher)
Created2014
Description
Assemblers and compilers provide feedback to a programmer in the form of error messages. These error messages become input to the debugging model of the programmer. For the programmer to fix an error, they should first locate the error in the program, understand what is causing that error, and finally resolve that error. Error messages play an important role in all three stages of fixing of errors. This thesis studies the effects of error messages in the context of teaching programming. Given an error message, this work investigates how it effects student’s way of 1) understanding the error, and 2) fixing the error. As part of the study, three error message types were developed – Default, Link and Example, to better understand the effects of error messages. The Default type provides an assembler-centric single line error message, the Link type provides a program-centric detailed error description with a hyperlink for more information, and the Example type provides a program centric detailed error description with a relevant example. All these error message types were developed for assembly language programming. A think aloud programming exercise was conducted as part of the study to capture the student programmer’s knowledge model. Different codes were developed to analyze the data collected as part of think aloud exercise. After transcribing, coding, and analyzing the data, it was found that the Link type of error message helped to fix the error in less time and with fewer steps. Among the three types, the Link type of error message also resulted in a significantly higher ratio of correct to incorrect steps taken by the programmer to fix the error.
ContributorsBeejady Murthy Kadekar, Harsha Kadekar (Author) / Sohoni, Sohum (Thesis advisor) / Craig, Scotty D. (Committee member) / Jordan, Shawn S (Committee member) / Gary, Kevin A (Committee member) / Arizona State University (Publisher)
Created2017
Description
The American Heart Association (AHA) estimates that there are approximately 200,000 in-hospital cardiac arrests (IHCA) annually with low rates of survival to discharge at about 22%. Training programs for cardiac arrest teams, also termed code teams, have been recommended by the Institute of Medicine (IOM) and in the AHA's consensus statement to help improve these dismal survival rates. Historically, training programs in the medical field are procedural in nature and done at the individual level, despite the fact that healthcare providers frequently work in teams. The rigidity of procedural training can cause habituation and lead to poor team performance if the situation does not match the original training circumstances. Despite the need for team training, factors such as logistics, time, personnel coordination, and financial constraints often hinder resuscitation team training. This research was a three-step process of: 1) development of a metric specific for the evaluation of code team performance, 2) development of a communication model that targeted communication and leadership during a code blue resuscitation, and 3) training and evaluation of the code team leader using the communication model. This research forms a basis to accomplish a broad vision of improving outcomes of IHCA events by applying conceptual and methodological strategies learned from collaborative and inter-disciplinary science of teams.
ContributorsHinski, Sandra T. (Author) / Cooke, Nancy J. (Thesis advisor) / Roscoe, Rod (Committee member) / Bekki, Jennifer (Committee member) / Arizona State University (Publisher)
Created2017
Description
Each programming language has a compiler associated with it which helps to identify logical or syntactical errors in the program. These compiler error messages play important part in the form of formative feedback for the programmer. Thus, the error messages should be constructed carefully, considering the affective and cognitive needs of programmers. This is especially true for systems that are used in educational settings, as the messages are typically seen by students who are novice programmers. If the error messages are hard to understand then they might discourage students from understanding or learning the programming language. The primary goal of this research is to identify methods to make the error messages more effective so that students can understand them better and simultaneously learn from their mistakes. This study is focused on understanding how the error message affects the understanding of the error and the approach students take to solve the error. In this study, three types of error messages were provided to the students. The first type is Default type error message which is an assembler centric error message. The second type is Link type error message which is a descriptive error message along with a link to the appropriate section of the PLP manual. The third type is Example type error message which is again a descriptive error message with an example of the similar type of error along with correction step. All these error types were developed for the PLP assembly language. A think-aloud experiment was designed and conducted on the students. The experiment was later transcribed and coded to understand different approach students take to solve different type of error message. After analyzing the result of the think-aloud experiment it was found that student read the Link type error message completely and they understood and learned from the error message to solve the error. The results also indicated that Link type was more helpful compare to other types of error message. The Link type made error solving process more effective compared to other error types.
ContributorsTanpure, Siddhant Bapusaheb (Author) / Sohoni, Sohum (Thesis advisor) / Gary, Kevin A (Committee member) / Craig, Scotty D. (Committee member) / Arizona State University (Publisher)
Created2018
Description
The current study investigated how multimedia pacing (learner-control versus system-paced) and presentation styles (visual-only versus audio/visual) impact learning physics concept material, mental effort, and self-efficacy. This 2X2 factorial study randomly assigned participants into one of four conditions that manipulated presentation style (visual-only versus audio/visual) and pacing of the content (system-paced versus learning-controlled). Participant's learning was measured by recording their retention of information and ability to transfer information. Measures of perceived difficulty (mental effort) and perceived ability (self-efficacy) were also obtained. No significant effects were observed in this study which doesn’t support the existence of either the modality or reverse modality effect at least in these noisier online learning environments. In addition, the hypothesis that their effects could be an artifact of experimental design could not be proven as the learner control condition did not yield any significant results.
ContributorsKrause, Tyler (Author) / Craig, Scotty D. (Thesis advisor) / Gray, Robert (Committee member) / Branaghan, Russell (Committee member) / Arizona State University (Publisher)
Created2018
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 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
Description
Multimedia learning has become increasingly popular as it proceeds to understand how different senses such as the visual and auditory systems work together to present information. The aim of the present study was to examine the effect of temporal contiguity, a principle of multimedia learning, while displaying images and narration of fruits and vegetables to increase memorization of content. 21 preschool students between the ages of 4 and 5 from Arizona State University’s Child Study Lab were recruited for the purpose of the study. Students received one of two versions of a short video while inside the classroom. The two videos displayed information either at the same time or successively. Children’s knowledge was assessed with a drag and drop categorization game. The findings show there were no significant differences between the two conditions. Future studies should consider a longer training period when developing multimedia learning technology to ensure content is retained.
ContributorsLang, Destiny Hope (Author) / Craig, Scotty D. (Thesis advisor) / Roscoe, Rod (Committee member) / Kupfer, Anne (Committee member) / Arizona State University (Publisher)
Created2019