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This study empirically evaluated the effectiveness of the instructional design, learning tools, and role of the teacher in three versions of a semester-long, high-school remedial Algebra I course to determine what impact self-regulated learning skills and learning pattern training have on students' self-regulation, math achievement, and motivation. The 1st version was a business-as-usual traditional classroom teaching mathematics with direct instruction. The 2rd version of the course provided students with self-paced, individualized Algebra instruction with a web-based, intelligent tutor. The 3rd version of the course coupled self-paced, individualized instruction on the web-based, intelligent Algebra tutor coupled with a series of e-learning modules on self-regulated learning knowledge and skills that were distributed throughout the semester. A quasi-experimental, mixed methods evaluation design was used by assigning pre-registered, high-school remedial Algebra I class periods made up of an approximately equal number of students to one of the three study conditions or course versions: (a) the control course design, (b) web-based, intelligent tutor only course design, and (c) web-based, intelligent tutor + SRL e-learning modules course design. While no statistically significant differences on SRL skills, math achievement or motivation were found between the three conditions, effect-size estimates provide suggestive evidence that using the SRL e-learning modules based on ARCS motivation model (Keller, 2010) and Let Me Learn learning pattern instruction (Dawkins, Kottkamp, & Johnston, 2010) may help students regulate their learning and improve their study skills while using a web-based, intelligent Algebra tutor as evidenced by positive impacts on math achievement, motivation, and self-regulated learning skills. The study also explored predictive analyses using multiple regression and found that predictive models based on independent variables aligned to student demographics, learning mastery skills, and ARCS motivational factors are helpful in defining how to further refine course design and design learning evaluations that measure achievement, motivation, and self-regulated learning in web-based learning environments, including intelligent tutoring systems.
ContributorsBarrus, Angela (Author) / Atkinson, Robert K (Thesis advisor) / Van de Sande, Carla (Committee member) / Savenye, Wilhelmina (Committee member) / Arizona State University (Publisher)
Created2013
Description
Concerted efforts have been made within teacher preparation programs to integrate teaching with technology into the curriculum. Unfortunately, these efforts continue to fall short as teachers' application of educational technology is unsophisticated and not well integrated. The most prevalent approaches to integrating technology tend to ignore pedagogy and content and assume that the technology integration knowledge for all contexts is the same. One theoretical framework that does acknowledge content, pedagogy, and context in conjunction with technology is Technological Pedagogical Content Knowledge (TPACK) and was the lens through which teacher development was measured and interpreted in this study. The purpose of this study was to investigate graduate teacher education students' knowledge and practice of teaching with technology as well as how that knowledge and practice changes after participation in an educational technology course. This study used a mixed-methods sequential explanatory research design in which both quantitative and qualitative data were gathered from 82 participants. TPACK pre- and postcourse surveys were administered to a treatment group enrolled in an educational technology course and to a nonequivalent control group enrolled in a learning theories course. Additionally, pre- and postcourse lesson plans were collected from the treatment group. Select treatment group participants also participated in phone interviews. Analyses compared pre- and post-course survey response differences within and between the treatment and control groups. Pre- and postlesson plan rubric score differences were compared within the treatment group. Quantitative text analyses were performed on the collected lesson plans. Open and axial coding procedures were followed to analyze interview transcripts. The results of the study revealed five significant findings: 1) graduate students entering an educational technology course reported lower ability in constructs related to teaching with technology than in constructs related to teaching in a traditional setting; 2) TPACK was malleable and TPACK instruments were sensitive to that malleability; 3) significant gains in reported and demonstrated TPACK constructs were found after participating in an educational technology course; 4) TPACK construct ability levels vary significantly by participant characteristics; and 5) influences on teaching knowledge and practice range from internet resources, to mentor teachers, and to standardized curriculum packages.
ContributorsSabo, Kent (Author) / Atkinson, Robert (Thesis advisor) / Archambault, Leanna (Committee member) / Savenye, Wilhelmina (Committee member) / Arizona State University (Publisher)
Created2013
Description
The use of educational technologies as a tool to improve academic achievement continues to increase as more technologies becomes available to students. However, teachers are entering the classroom not fully prepared to integrate technology into their daily classroom teaching because they have not been adequately prepared to do so. Teacher preparation programs are falling short in this area because educational technology and the role of technology in the classroom is seen as an extra component to daily teaching rather than a central one. Many teacher preparation programs consist of one stand-alone educational technology course that is expected to prepare teachers to integrate technology in their future classrooms. Throughout the remainder of the program, the teachers are not seeing educational technologies modeled in their other core courses, nor are they getting the hands-on interaction necessary to become more confident in using these technologies with their future students. The purpose of this study was to examine teachers' views of educational technology in the classroom from those enrolled in a graduate program. The study consisted 74 first- and second-year teachers who were enrolled an alternative teacher preparation program. Thirty-four of the teachers received the Integrating Curriculum and Technology (iCAT) intervention and the remaining 40 teachers were part of the control group. Each teacher completed a pre- and post-intervention questionnaire and 23 of the 74 teachers participated in one of three focus group interviews. Additional data from the teachers' course instructors were gathered and analyzed to compliment the focus group and quantitative data. Results showed that iCAT participants' scores for confidence in using technology and efficacy for using educational technology increased at a faster rate than the control group participants' scores. Similarly, confidence in using technology, perceptions about integrating technology in the classroom, and efficacy for using educational technology could be predicted by the amount of hands-on interaction with technology that the teachers received during their graduate course. The discussion focuses on recommendations for infusing technology throughout teacher preparation programs so that teachers have the tools to prepare their students to use a variety of technologies so that their students can be better prepared to complete in today's workforce.
ContributorsKisicki, Todd (Author) / Wetzel, Keith (Thesis advisor) / Bitter, Gary (Thesis advisor) / Buss, Ray (Committee member) / Savenye, Wilhelmina (Committee member) / Arizona State University (Publisher)
Created2012
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
This study collected and examined information on K-12 teachers currently involved in online education in the United States. The purposes of this study included defining the demographics of these teachers, determining the extent to which they were formally educated and/or trained to teach online, and to compare these findings to those from a similar study conducted six years earlier. A web-based survey, including questions in both open and closed form, was used to gather data from 325 participants currently teaching at least one online class at publicly funded K-12 online schools nationwide. Survey questions covered the following six domains: a) personal demographics, b) educational background and experience, c) pre-service training, d) in-service training, and e) current online teaching assignments. The results of this study indicate that those currently teaching online to K-12 students have demographic characteristics that are similar to face-to-face teachers, particularly in terms of gender, age, and ethnicity/race; however, the online teachers generally had higher levels of educational attainment, more years of teaching experience, and were significantly more likely to teach on a part-time basis. It was found that teachers working with K-12 students online are self-motivated, place a high value on learning and education, and enjoy the challenge and process of using technology for this purpose. Based on findings, only a limited number of university-based teacher preparation programs address any aspect of the methods and techniques required for teaching online, and even fewer offer online field placement opportunities for pre-service teachers. For the most part, current online teachers were found to have received training after graduation, while working in the field. Further research is needed to specifically define and empirically validate the methods and techniques required for effective online teaching at the K-12 levels so that formal educational and training programs can be further developed to effectively prepare future K-12 online teachers.
ContributorsLarson, Jean Sutton (Author) / Archambault, Leanna (Thesis advisor) / Savenye, Wilhelmina (Thesis advisor) / Bitter, Gary (Committee member) / Arizona State University (Publisher)
Created2014
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
There has been a lot of research in the field of artificial intelligence about thinking machines. Alan Turing proposed a test to observe a machine's intelligent behaviour with respect to natural language conversation. The Winograd schema challenge is suggested as an alternative, to the Turing test. It needs inferencing capabilities, reasoning abilities and background knowledge to get the answer right. It involves a coreference resolution task in which a machine is given a sentence containing a situation which involves two entities, one pronoun and some more information about the situation and the machine has to come up with the right resolution of a pronoun to one of the entities. The complexity of the task is increased with the fact that the Winograd sentences are not constrained by one domain or specific sentence structure and it also contains a lot of human proper names. This modification makes the task of association of entities, to one particular word in the sentence, to derive the answer, difficult. I have developed a pronoun resolver system for the confined domain Winograd sentences. I have developed a classifier or filter which takes input sentences and decides to accept or reject them based on a particular criteria. Once the sentence is accepted. I run parsers on it to obtain the detailed analysis. Furthermore I have developed four answering modules which use world knowledge and inferencing mechanisms to try and resolve the pronoun. The four techniques I use are : ConceptNet knowledgebase, Search engine pattern counts,Narrative event chains and sentiment analysis. I have developed a particular aggregation mechanism for the answers from these modules to arrive at a final answer. I have used caching technique for the association relations that I obtain for different modules, so as to boost the performance. I run my system on the standard ‘nyu dataset’ of Winograd sentences and questions. This dataset is then restricted, by my classifier, to 90 sentences. I evaluate my system on this 90 sentence dataset. When I compare my results against the state of the art system on the same dataset, I get nearly 4.5 % improvement in the restricted domain.
ContributorsBudukh, Tejas Ulhas (Author) / Baral, Chitta (Thesis advisor) / VanLehn, Kurt (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2013
Description
This study investigated the effects of concurrent audio and equivalent onscreen text on the ability of learners of English as a foreign language (EFL) to form associations between textual and aural forms of target vocabulary words. The study also looked at the effects of learner control over an audio sequence on the association of textual and aural forms of target words. Attitudes towards experimental treatments and reported level of cognitive load were also examined in the context of a computer-based multimedia instructional program. A total of 200 college students took part in the study. Participants were randomly assigned to experimental conditions in a 2 x 3 factorial design with level of learner control (learner-controlled vs. not-learner-controlled) and format of presentation of information (audio + no text vs. audio + full text vs. audio + keyword text) as factors. The subjects completed a pretest, a posttest, cognitive load questions, and an attitude questionnaire. The results revealed the following findings: (a) groups in the audio + keyword text conditions outperformed those in the audio + no text and audio + full text conditions on text-sound association, (b) within the audio + keyword text conditions, the learner-controlled group outperformed the not-learner-controlled group on text-sound association, (c) within the learner-controlled conditions, the audio + keyword group outperformed the audio + no text and audio + full text groups on text-sound association, (d) a redundancy effect was not found for any treatment condition, and (e) overall, participants had positive attitudes towards the treatments. Implications, limitations, and future directions are discussed within the frameworks of cognitive load theory and cognitive theory of multimedia learning.
ContributorsEnciso Bernal, Ana Maria (Author) / Nelson, Brian C. (Thesis advisor) / Savenye, Wilhelmina (Committee member) / Atkinson, Robert K. (Committee member) / Arizona State University (Publisher)
Created2014
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
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