Matching Items (5)
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- All Subjects: Online Education
- All Subjects: artificial intelligence
- Member of: Theses and Dissertations
- Status: Published
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
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
One of the core components of many video games is their artificial intelligence. Through AI, a game can tell stories, generate challenges, and create encounters for the player to overcome. Even though AI has continued to advance through the implementation of neural networks and machine learning, game AI tends to implement a series of states or decisions instead to give the illusion of intelligence. Despite this limitation, games can still generate a wide range of experiences for the player. The Hybrid Game AI Framework is an AI system that combines the benefits of two commonly used approaches to developing game AI: Behavior Trees and Finite State Machines. Developed in the Unity Game Engine and the C# programming language, this AI Framework represents the research that went into studying modern approaches to game AI and my own attempt at implementing the techniques learned. Object-oriented programming concepts such as inheritance, abstraction, and low coupling are utilized with the intent to create game AI that's easy to implement and expand upon. The final goal was to create a flexible yet structured AI data structure while also minimizing drawbacks by combining Behavior Trees and Finite State Machines.
ContributorsRamirez Cordero, Erick Alberto (Author) / Kobayashi, Yoshihiro (Thesis director) / Nelson, Brian (Committee member) / Computer Science and Engineering Program (Contributor) / Computing and Informatics Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
For this master's thesis, an open learner model is integrated with Quinn, a teachable robotic agent developed at Arizona State University. This system is represented as a feedback system, which aims to improve a student’s understanding of a subject. It also helps to understand the effect of the learner model when it is represented by performance of the teachable agent. The feedback system represents performance of the teachable agent, and not of a student. Data in the feedback system is thus updated according to a student's understanding of the subject. This provides students an opportunity to enhance their understanding of a subject by analyzing their performance. To test the effectiveness of the feedback system, student understanding in two different conditions is analyzed. In the first condition a feedback report is not provided to the students, while in the second condition the feedback report is provided in the form of the agent’s performance.
ContributorsUpadhyay, Abha (Author) / Walker, Erin (Thesis advisor) / Nelson, Brian (Committee member) / Amresh, Ashish (Committee member) / Arizona State University (Publisher)
Created2016
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