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- Creators: Mozart, Wolfgang Amadeus, 1756-1791
Description
The purpose of this study was to investigate the effects of instructor response prompts and rubrics on students' performance in an asynchronous discussion-board assignment, their learning achievement on an objective-type posttest, and their reported satisfaction levels. Researchers who have studied asynchronous computer-mediated student discussion transcripts have found evidence of mostly mid-level critical thinking skills, with fewer examples limited to lower or higher order thinking skill demonstration. Some researchers suggest that instructors may facilitate increased demonstration of higher-order critical thinking skills within asynchronous discussion-board activities. However, there is little empirical evidence available to compare the use of different external supports to facilitate students' critical thinking skills performance and learning achievement in blended learning environments. Results of the present study indicate that response prompts and rubrics can affect students' discussion performance, learning, and satisfaction ratings. The results, however, are complex, perhaps mirroring the complexity of instructor-led online learning environments. Regarding discussion board performance, presenting students with a rubric tended to yield higher scores on most aspects that is, on overall performance, as well as depth and breadth of performance, though these differences were not significant. In contrast, instructor prompts tended to yield lower scores on aspects of discussion board performance. On breadth, in fact, this main effect difference was significant. Interactions also indicated significant differences on several aspects of discussion board performance, in most cases indicating that the combination of rubric and prompt was detrimental to scores. The learning performance on the quiz showed, again, the effectiveness of rubrics, with students who received the rubric earning significantly higher scores, and with no main effects or interactions for instructor prompts. Regarding student satisfaction, again, the picture is complicated. Results indicated that, in some instances, the integration of prompts resulted in lower satisfaction ratings, particularly in the areas of students' perceptions of the amount of work required, learning in the partially online format, and student-to-student interaction. Based on these results, design considerations to support rubric use and explicit feedback in asynchronous discussions to support student learning are proposed.
ContributorsGiacumo, Lisa (Author) / Savenye, Wilhelmina (Thesis advisor) / Nelson, Brian (Committee member) / Legacy, Jane (Committee member) / Bitter, Gary (Committee member) / Arizona State University (Publisher)
Created2012
Description
The purpose of this survey study was to collect data from pre-K-12 educators in the U.S. regarding their perceptions of the purpose, conceptions, use, impact, and results of educational research. The survey tool was based on existing questionnaires and case studies in the literature, as well as newly developed items. 3,908 educators in a database developed over 10+ years at the world's largest education company were sent a recruiting email; 400 elementary and secondary teachers in the final sample completed the online survey containing 48 questions over a three-week deployment period in the spring of 2013. Results indicated that overall teachers believe educational research is important, that the most important purpose of research is to increase effectiveness of classroom practice, yet research is not frequently sought out during the course of practice. Teachers perceive results in research journals as the most trustworthy yet also perceive research journals the most difficult to access (relying second-most often for research via in-service trainings). These findings have implications for teachers, administrators, policy-makers, and researchers. Educational researchers should seek to address both the theoretical and the applied aspects of learning. Professional development must make explicit links between research findings and classroom strategies and tactics, and research must be made more readily available to those who are not currently seeking additional credentialing, and therefore do not individually have access to scholarly literature. Further research is needed to expand the survey sample and refine the survey instrument. Similar research with administrators in pre-K-20 settings as well as in-depth interviews would serve to investigate the "why" of many findings.
ContributorsMahoney, Shawn (Author) / Savenye, Wilhelmina (Thesis advisor) / Nelson, Brian (Committee member) / Atkinson, Robert (Committee member) / Arizona State University (Publisher)
Created2013
Description
Mobile apps have improved human lifestyle in various aspects ranging from instant messaging to tele-health. In the current app development paradigm, apps are being developed individually and agnostic of each other. The goal of this thesis is to allow a new world where multiple apps communicate with each other to achieve synergistic benefits. To enable integration between apps, manual communication between developers is needed, which can be problematic on many levels. In order to promote app integration, a systematic approach towards data sharing between multiple apps is essential. However, current approaches to app integration require large code modifications to reap the benefits of shared data such as requiring developers to provide APIs or use large, invasive middlewares. In this thesis, a data sharing framework was developed providing a non-invasive interface between mobile apps for data sharing and integration. A separate app acts as a registry to allow apps to register database tables to be shared and query this information. Two health monitoring apps were developed to evaluate the sharing framework and different methods of data integration between apps to promote synergistic feedback. The health monitoring apps have shown non-invasive solutions can provide data sharing functionality without large code modifications and manual communication between developers.
ContributorsMilazzo, Joseph (Author) / Gupta, Sandeep K.S. (Thesis advisor) / Varsamopoulos, Georgios (Committee member) / Nelson, Brian (Committee member) / Arizona State University (Publisher)
Created2014
Description
With the unveiling of the National Educational Technology Plan 2010, both preservice and inservice K12 teachers in the United States are expected to create a classroom environment that fosters the creation of digital citizens. However, it is unclear whether or not teacher education programs build this direct instruction, or any other method of introducing students to the National Education Technology Standards (NETS), "a standard of excellence and best practices in learning, teaching and leading with technology in education," into their curriculum (International Society for Technology in Education, 2012). As with most teaching skills, the NETS and standards-based technology integration must be learned through exposure during the teacher preparation curriculum, either through modeling, direct instruction or assignments constructed to encourage standards-based technology integration. This study attempted to determine the extent to which preservice teachers at Arizona State University (ASU) enrolled in the Mary Lou Fulton Teachers College (MLFTC) can recognize the National Education Technology Standards (NETS) published by the International Society for Technology in Education (ISTE) and to what extent preservice teachers are exposed to technology integration in accordance with the NETS-T standards in their preparation curriculum in order to answer the questions of whether or not teacher education curriculum provides students an opportunity to learn and apply the NETS-T and if preservice teachers in core teacher preparation program courses that include objectives that integrate technology are more likely to be able to identify NETS-T standards than those in courses that do not include these elements In order to answer these questions, a mixed-method design study was utilized to gather data from an electronic survey, one-on-one interviews with students, faculty, and administrators, and document analysis of core course objectives and curriculum goals in the teacher certification program at ASU. The data was analyzed in order to determine the relationship between the preservice teachers, the NETS-T standards, and the role technology plays in the curriculum of the teacher preparation program. Results of the analysis indicate that preservice teachers have a minimum NETS-T awareness at the Literacy level, indicating that they can use technology skills when prompted and explore technology independently.
ContributorsLewis, Carrie L (Author) / Nelson, Brian (Thesis advisor) / Archambault, Leanna (Thesis advisor) / Savenye, Wilhelmenia (Committee member) / Atkinson, Robert (Committee member) / Arizona State University (Publisher)
Created2013
ContributorsMozart, Wolfgang Amadeus, 1756-1791 (Composer)
Description
This study explored three methods to measure cognitive load in a learning environment using four logic puzzles that systematically varied in level of intrinsic cognitive load. Participants' perceived intrinsic load was simultaneously measured with a self-report measure--a traditional subjective measure--and two objective, physiological measures based on eye-tracking and EEG technology. In addition to gathering self-report, eye-tracking data, and EEG data, this study also captured data on individual difference variables and puzzle performance. Specifically, this study addressed the following research questions: 1. Are self-report ratings of cognitive load sensitive to tasks that increase in level of intrinsic load? 2. Are physiological measures sensitive to tasks that increase in level of intrinsic load? 3. To what extent do objective physiological measures and individual difference variables predict self-report ratings of intrinsic cognitive load? 4. Do the number of errors and the amount of time spent on each puzzle increase as the puzzle difficulty increases? Participants were 56 undergraduate students. Results from analyses with inferential statistics and data-mining techniques indicated features from the physiological data were sensitive to the puzzle tasks that varied in level of intrinsic load. The self-report measures performed similarly when the difference in intrinsic load of the puzzles was the most varied. Implications for these results and future directions for this line of research are discussed.
ContributorsJoseph, Stacey (Author) / Atkinson, Robert K (Thesis advisor) / Johnson-Glenberg, Mina (Committee member) / Nelson, Brian (Committee member) / Klein, James (Committee member) / Arizona State University (Publisher)
Created2013
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
For this master's thesis, a unique set of cognitive prompts, designed to be delivered through a teachable robotic agent, were developed for students using Tangible Activities for Geometry (TAG), a tangible learning environment developed at Arizona State University. The purpose of these prompts is to enhance the affordances of the tangible learning environment and help researchers to better understand how we can design tangible learning environments to best support student learning. Specifically, the prompts explicitly encourage users to make use of their physical environment by asking students to perform a number of gestures and behaviors while prompting students about domain-specific knowledge. To test the effectiveness of these prompts that combine elements of cognition and physical movements, the performance and behavior of students who encounter these prompts while using TAG will be compared against the performance and behavior of students who encounter a more traditional set of cognitive prompts that would typically be used within a virtual learning environment. Following this study, data was analyzed using a novel modeling and analysis tool that combines enhanced log annotation using video and user model generation functionalities to highlight trends amongst students.
ContributorsThomas, Elissa (Author) / Burleson, Winslow (Thesis advisor) / Muldner, Katarzyna (Committee member) / Walker, Erin (Committee member) / Glenberg, Arthur (Committee member) / Arizona State University (Publisher)
Created2014
Description
Research in the learning sciences suggests that students learn better by collaborating with their peers than learning individually. Students working together as a group tend to generate new ideas more frequently and exhibit a higher level of reasoning. In this internet age with the advent of massive open online courses (MOOCs), students across the world are able to access and learn material remotely. This creates a need for tools that support distant or remote collaboration. In order to build such tools we need to understand the basic elements of remote collaboration and how it differs from traditional face-to-face collaboration.
The main goal of this thesis is to explore how spoken dialogue varies in face-to-face and remote collaborative learning settings. Speech data is collected from student participants solving mathematical problems collaboratively on a tablet. Spoken dialogue is analyzed based on conversational and acoustic features in both the settings. Looking for collaborative differences of transactivity and dialogue initiative, both settings are compared in detail using machine learning classification techniques based on acoustic and prosodic features of speech. Transactivity is defined as a joint construction of knowledge by peers. The main contributions of this thesis are: a speech corpus to analyze spoken dialogue in face-to-face and remote settings and an empirical analysis of conversation, collaboration, and speech prosody in both the settings. The results from the experiments show that amount of overlap is lower in remote dialogue than in the face-to-face setting. There is a significant difference in transactivity among strangers. My research benefits the computer-supported collaborative learning community by providing an analysis that can be used to build more efficient tools for supporting remote collaborative learning.
The main goal of this thesis is to explore how spoken dialogue varies in face-to-face and remote collaborative learning settings. Speech data is collected from student participants solving mathematical problems collaboratively on a tablet. Spoken dialogue is analyzed based on conversational and acoustic features in both the settings. Looking for collaborative differences of transactivity and dialogue initiative, both settings are compared in detail using machine learning classification techniques based on acoustic and prosodic features of speech. Transactivity is defined as a joint construction of knowledge by peers. The main contributions of this thesis are: a speech corpus to analyze spoken dialogue in face-to-face and remote settings and an empirical analysis of conversation, collaboration, and speech prosody in both the settings. The results from the experiments show that amount of overlap is lower in remote dialogue than in the face-to-face setting. There is a significant difference in transactivity among strangers. My research benefits the computer-supported collaborative learning community by providing an analysis that can be used to build more efficient tools for supporting remote collaborative learning.
ContributorsNelakurthi, Arun Reddy (Author) / Pon-Barry, Heather (Thesis advisor) / VanLehn, Kurt (Committee member) / Walker, Erin (Committee member) / Arizona State University (Publisher)
Created2014
Description
This study aims to uncover whether English Central, an online English as a Second Language tool, improves speaking proficiency for undergraduate students with developing English skills. Eighty-three advanced English language learners from the American English and Culture Program at Arizona State University were randomly assigned to one of three conditions: the use of English Central with a learner-control, shared-control, and a no-treatment condition. The two treatment groups were assigned approximately 14.7 hours of online instruction. The relative impact of each of the three conditions was assessed using two measures. First, the Pearson Versant Test (www.versanttest.com), a well-established English-as-a-second-language speaking test, was administered to all of the participants as a pre- and post-test measure. Second, students were given a post-treatment questionnaire that measured their motivation in using online instruction in general, and English Central specifically. Since a significant teacher effect was found, teachers involved in this study were also interviewed in order to ascertain their attitude toward English Central as a homework tool. Learner outcomes were significantly different between the shared and learner conditions. Student motivation was predictive of learning outcomes. Subjects in the shared condition outperformed those in the learner condition. Furthermore, those in the shared condition scored higher than the control condition; however, this result did not reach statistical significance. Results of the follow-up teacher survey revealed that while a teacher's view of the tool (positive or negative), was not a predictor of student success, teacher presentation of the tool may lead to a significant impact on student learning outcomes.
ContributorsDixon, Shane Y. (Shane Yahlu) (Author) / Atkinson, Robert (Thesis advisor) / Savenye, Wilhelmina (Committee member) / Nelson, Brian (Committee member) / Arizona State University (Publisher)
Created2015