Matching Items (3)
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- All Subjects: Online Education
- Creators: Bitter, Gary
- Creators: Butler, Nicholas
- Member of: Theses and Dissertations
- Status: Published
Description
This dissertation study quantitatively measured the performance of 345 students who received public speaking instruction through an online platform presented in one of six experimental conditions in order to explore the ability of online lectures to replicate the characteristics of instructor presence and learner interaction traditionally associated with face-to-face public speaking courses. The study investigated the following research questions:
RQ1: How does the visibility of an instructor in a public speaking video lesson affect students' perception of presence?
RQ2: How does the visibility of an instructor in a public speaking video lesson affect student learning?
RQ3: How do self-explanation (Constructive) and note-taking (Active) types of learning activities affect students' perception of presence compared to passive lessons when presented in a video lesson?
RQ4: How do self-explanation (Constructive) and note-taking (Active) types of learning activities affect student learning compared to passive lessons when presented in a video lesson?
Additionally, the study collected qualitative feedback from participants on their experience in order to improve understanding of how to effectively design lectures for public speaking courses.
Results of the study were unable to statistically distinguish between students assigned to treatments that varied in both modality and level of activity. However, a significant finding of this study is that learning gains and students' perception of instructor presence were positive across all conditions.
The lack of significant differences by treatment indicates that the design attributes at the center of the study may be unnecessary considerations for developing content for online learning. Consequently, the improved performance of participants regardless of their assigned treatment in this study identifies a limitation to the application of Media Equation Theory and the Interactive-Constructive-Active-Passive (ICAP) Framework for designing online learning content for public speaking students as well as identifies two key implications: 1) exposure to an online lesson can increase learning; and 2) exposure to an online lesson can serve as a cost-effective alternative for producing lessons in public speaking courses.
RQ1: How does the visibility of an instructor in a public speaking video lesson affect students' perception of presence?
RQ2: How does the visibility of an instructor in a public speaking video lesson affect student learning?
RQ3: How do self-explanation (Constructive) and note-taking (Active) types of learning activities affect students' perception of presence compared to passive lessons when presented in a video lesson?
RQ4: How do self-explanation (Constructive) and note-taking (Active) types of learning activities affect student learning compared to passive lessons when presented in a video lesson?
Additionally, the study collected qualitative feedback from participants on their experience in order to improve understanding of how to effectively design lectures for public speaking courses.
Results of the study were unable to statistically distinguish between students assigned to treatments that varied in both modality and level of activity. However, a significant finding of this study is that learning gains and students' perception of instructor presence were positive across all conditions.
The lack of significant differences by treatment indicates that the design attributes at the center of the study may be unnecessary considerations for developing content for online learning. Consequently, the improved performance of participants regardless of their assigned treatment in this study identifies a limitation to the application of Media Equation Theory and the Interactive-Constructive-Active-Passive (ICAP) Framework for designing online learning content for public speaking students as well as identifies two key implications: 1) exposure to an online lesson can increase learning; and 2) exposure to an online lesson can serve as a cost-effective alternative for producing lessons in public speaking courses.
ContributorsButler, Nicholas (Author) / Nelson, Brian (Thesis advisor) / Atkinson, Robert (Committee member) / Savenye, Wilhelmina (Committee member) / Arizona State University (Publisher)
Created2014
Description
While predicting completion in Massive Open Online Courses (MOOCs) has been an active area of research in recent years, predicting completion in self-paced MOOCS, the fastest growing segment of open online courses, has largely been ignored. Using learning analytics and educational data mining techniques, this study examined data generated by over 4,600 individuals working in a self-paced, open enrollment college algebra MOOC over a period of eight months.
Although just 4% of these students completed the course, models were developed that could predict correctly nearly 80% of the time which students would complete the course and which would not, based on each student’s first day of work in the online course. Logistic regression was used as the primary tool to predict completion and focused on variables associated with self-regulated learning (SRL) and demographic variables available from survey information gathered as students begin edX courses (the MOOC platform employed).
The strongest SRL predictor was the amount of time students spent in the course on their first day. The number of math skills obtained the first day and the pace at which these skills were gained were also predictors, although pace was negatively correlated with completion. Prediction models using only SRL data obtained on the first day in the course correctly predicted course completion 70% of the time, whereas models based on first-day SRL and demographic data made correct predictions 79% of the time.
Although just 4% of these students completed the course, models were developed that could predict correctly nearly 80% of the time which students would complete the course and which would not, based on each student’s first day of work in the online course. Logistic regression was used as the primary tool to predict completion and focused on variables associated with self-regulated learning (SRL) and demographic variables available from survey information gathered as students begin edX courses (the MOOC platform employed).
The strongest SRL predictor was the amount of time students spent in the course on their first day. The number of math skills obtained the first day and the pace at which these skills were gained were also predictors, although pace was negatively correlated with completion. Prediction models using only SRL data obtained on the first day in the course correctly predicted course completion 70% of the time, whereas models based on first-day SRL and demographic data made correct predictions 79% of the time.
ContributorsCunningham, James Allan (Author) / Bitter, Gary (Thesis advisor) / Barber, Rebecca (Committee member) / Douglas, Ian (Committee member) / Arizona State University (Publisher)
Created2017
Description
Due to its difficult nature, organic chemistry is receiving much research attention across the nation to develop more efficient and effective means to teach it. As part of that, Dr. Ian Gould at ASU is developing an online organic chemistry educational website that provides help to students, adapts to their responses, and collects data about their performance. This thesis creative project addresses the design and implementation of an input parser for organic chemistry reagent questions, to appear on his website. After students used the form to submit questions throughout the Spring 2013 semester in Dr. Gould's organic chemistry class, the data gathered from their usage was analyzed, and feedback was collected. The feedback obtained from students was positive, and suggested that the input parser accomplished the educational goals that it sought to meet.
ContributorsBeerman, Eric Christopher (Author) / Gould, Ian (Thesis director) / Wilkerson, Kelly (Committee member) / Mosca, Vince (Committee member) / Barrett, The Honors College (Contributor) / Computer Science and Engineering Program (Contributor)
Created2013-05