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- All Subjects: Collaboration
Description
This thesis is an initial test of the hypothesis that superficial measures suffice for measuring collaboration among pairs of students solving complex math problems, where the degree of collaboration is categorized at a high level. Data were collected
in the form of logs from students' tablets and the vocal interaction between pairs of students. Thousands of different features were defined, and then extracted computationally from the audio and log data. Human coders used richer data (several video streams) and a thorough understand of the tasks to code episodes as
collaborative, cooperative or asymmetric contribution. Machine learning was used to induce a detector, based on random forests, that outputs one of these three codes for an episode given only a characterization of the episode in terms of superficial features. An overall accuracy of 92.00% (kappa = 0.82) was obtained when
comparing the detector's codes to the humans' codes. However, due irregularities in running the study (e.g., the tablet software kept crashing), these results should be viewed as preliminary.
in the form of logs from students' tablets and the vocal interaction between pairs of students. Thousands of different features were defined, and then extracted computationally from the audio and log data. Human coders used richer data (several video streams) and a thorough understand of the tasks to code episodes as
collaborative, cooperative or asymmetric contribution. Machine learning was used to induce a detector, based on random forests, that outputs one of these three codes for an episode given only a characterization of the episode in terms of superficial features. An overall accuracy of 92.00% (kappa = 0.82) was obtained when
comparing the detector's codes to the humans' codes. However, due irregularities in running the study (e.g., the tablet software kept crashing), these results should be viewed as preliminary.
ContributorsViswanathan, Sree Aurovindh (Author) / VanLehn, Kurt (Thesis advisor) / T.H CHI, Michelene (Committee member) / Walker, Erin (Committee member) / Arizona State University (Publisher)
Created2014
Description
The purpose of this thesis is to understand peer-to-peer study habits at Arizona State University, and provide recommendations for improving these habits through online integration. This was done by researching current peer-to-peer collaboration literature, and analyzing online integration efforts. Interviews of Arizona State University students were carried out in order to discover specific insights on study patterns at this university. The scope of this research study was further limited to freshman and sophomore engineering, mathematics, and science majors in order to mitigate the impacts of external factors. The background research and study illuminated various flaws in existing peer-to-peer collaboration tools and methods. These weaknesses were then used to design two online tools that would be incorporated into a student resource dashboard. The first tool, called "Ask a Peer", provides a question and answer forum for students. This tool differs from existing products because it provides a mobile platform for students to receive reputable and immediate responses from their classmates. The second tool, "Study Buddy Finder", can be used by students to form study partnerships. This tool is beneficial because it displays information that is essential to students deciding to work together. The thesis provides detailed designs for both modules, and provides the foundation for implementation.
ContributorsPatel, Niraj (Author) / Balasooriya, Janaka (Thesis director) / Eaton, John (Committee member) / Walker, Erin (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor)
Created2013-12
Description
Despite the advancement of online tools for activities related to the core experience of taking classes on a college campus, there has been a relatively small amount of research into implementing online tools for ancillary academic resources (e.g. tutoring centers, review sessions, etc.). Previous work and a study conducted for this paper indicates that there is value in creating these online tools but that there is value in maintaining an in-person component to these services. Based on this, a system which provides personalized, easily-accessible, simple access to these services is proposed. Designs for user-centered online-tools that provides access to and interaction with tutoring centers and review sessions are described and prototypes are developed to demonstrate the application of design principles for online tools for academic services.
ContributorsBerk, Nicholas Robert (Author) / Balasooriya, Janaka (Thesis director) / Eaton, John (Committee member) / Walker, Erin (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-12
Description
Virtual Reality (hereafter VR) and Mixed Reality (hereafter MR) have opened a new line of applications and possibilities. Amidst a vast network of potential applications, little research has been done to provide real time collaboration capability between users of VR and MR. The idea of this thesis study is to develop and test a real time collaboration system between VR and MR. The system works similar to a Google document where two or more users can see what others are doing i.e. writing, modifying, viewing, etc. Similarly, the system developed during this study will enable users in VR and MR to collaborate in real time.
The study of developing a real-time cross-platform collaboration system between VR and MR takes into consideration a scenario in which multiple device users are connected to a multiplayer network where they are guided to perform various tasks concurrently.
Usability testing was conducted to evaluate participant perceptions of the system. Users were required to assemble a chair in alternating turns; thereafter users were required to fill a survey and give an audio interview. Results collected from the participants showed positive feedback towards using VR and MR for collaboration. However, there are several limitations with the current generation of devices that hinder mass adoption. Devices with better performance factors will lead to wider adoption.
The study of developing a real-time cross-platform collaboration system between VR and MR takes into consideration a scenario in which multiple device users are connected to a multiplayer network where they are guided to perform various tasks concurrently.
Usability testing was conducted to evaluate participant perceptions of the system. Users were required to assemble a chair in alternating turns; thereafter users were required to fill a survey and give an audio interview. Results collected from the participants showed positive feedback towards using VR and MR for collaboration. However, there are several limitations with the current generation of devices that hinder mass adoption. Devices with better performance factors will lead to wider adoption.
ContributorsSeth, Nayan Sateesh (Author) / Nelson, Brian (Thesis advisor) / Walker, Erin (Committee member) / Atkinson, Robert (Committee member) / Arizona State University (Publisher)
Created2017
Description
Computational thinking, the fundamental way of thinking in computer science, including information sourcing and problem solving behind programming, is considered vital to children who live in a digital era. Most of current educational games designed to teach children about coding either rely on external curricular materials or are too complicated to work well with young children. In this thesis project, Guardy, an iOS tower defense game, was developed to help children over 8 years old learn about and practice using basic concepts in programming. The game is built with the SpriteKit, a graphics rendering and animation infrastructure in Apple’s integrated development environment Xcode. It simplifies switching among different game scenes and animating game sprites in the development. In a typical game, a sequence of operations is arranged by players to destroy incoming enemy minions. Basic coding concepts like looping, sequencing, conditionals, and classification are integrated in different levels. In later levels, players are required to type in commands and put them in an order to keep playing the game. To reduce the difficulty of the usability testing, a method combining questionnaires and observation was conducted with two groups of college students who either have no programming experience or are familiar with coding. The results show that Guardy has the potential to help children learn programming and practice computational thinking.
ContributorsWang, Xiaoxiao (Author) / Nelson, Brian C. (Thesis advisor) / Turaga, Pavan (Committee member) / Walker, Erin (Committee member) / Arizona State University (Publisher)
Created2017
Description
Electronic books or eBooks have the potential to revolutionize the way humans read and learn. eBooks offer many advantages such as simplicity, ease of use, eco-friendliness, and portability. The advancement of technology has introduced many forms of multimedia objects into eBooks, which may help people learn from them. To help the readers understand and comprehend a concept that is put forward by the author of an eBook, there is ongoing research involving the use of augmented reality (AR) in education. This study explores how AR and three-dimensional interactive models are integrated into eBooks to help the readers comprehend the content quickly and swiftly. It compares the reading activities of people when they experience these two visual representations within an eBook.
This study required participants to interact with some instructional material presented on an eBook and complete a learning measure. While interacting with the eBook, participants were equipped with a set of physiological devices, namely an ABM EEG headset and eye tracker during the experiment to collect biometric data that could be used to objectively measure their user experience. Fifty college students participated in this study. The data collected from each of the participants was used to analyze the reading activities of people by performing an Independent Samples t-test.
This study required participants to interact with some instructional material presented on an eBook and complete a learning measure. While interacting with the eBook, participants were equipped with a set of physiological devices, namely an ABM EEG headset and eye tracker during the experiment to collect biometric data that could be used to objectively measure their user experience. Fifty college students participated in this study. The data collected from each of the participants was used to analyze the reading activities of people by performing an Independent Samples t-test.
ContributorsJuluru, Kalyan Kumar (Author) / Atkinson, Robert K. (Thesis advisor) / Chen, Yinong (Thesis advisor) / Walker, Erin (Committee member) / Arizona State University (Publisher)
Created2017
Description
Students seldom spontaneously collaborate with each other. A system that can measure collaboration in real time could be useful, for example, by helping the teacher locate a group requiring guidance. To address this challenge, the research presented here focuses on building and comparing collaboration detectors for different types of classroom problem solving activities, such as card sorting and handwriting.
Transfer learning using different representations was also studied with a goal of building collaboration detectors for one task can be used with a new task. Data for building such detectors were collected in the form of verbal interaction and user action logs from students’ tablets. Three qualitative levels of interactivity were distinguished: Collaboration, Cooperation and Asymmetric Contribution. Machine learning was used to induce a classifier that can assign a code for every episode based on the set of features. The results indicate that machine learned classifiers were reliable and can transfer.
Transfer learning using different representations was also studied with a goal of building collaboration detectors for one task can be used with a new task. Data for building such detectors were collected in the form of verbal interaction and user action logs from students’ tablets. Three qualitative levels of interactivity were distinguished: Collaboration, Cooperation and Asymmetric Contribution. Machine learning was used to induce a classifier that can assign a code for every episode based on the set of features. The results indicate that machine learned classifiers were reliable and can transfer.
ContributorsViswanathan, Sree Aurovindh (Author) / VanLehn, Kurt (Thesis advisor) / Hsiao, Ihan (Committee member) / Walker, Erin (Committee member) / D' Angelo, Cynthia (Committee member) / Arizona State University (Publisher)
Created2020