Browsing by Subject "Online learning"

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Business Plan Development for Online Learning
(University of Minnesota Extension Center for Youth Development, 2017) Robideau, Kari
This is a project planning guide for teams developing online learning environments. All of the components relate to each other and are organized in a way that encourages teams to discuss and determine which of the aspects fit with their online project. This planning guide is most helpful when considered prior to engaging in a design and development process.
Dynamic Learning from Time-Varying Social Networks
(2016-05) Baingana, Brian
One of the foremost intellectual challenges of this century is to understand the collective behavior of complex systems. Such systems are ubiquitous, and range from ``engineered systems'' including the Internet and online social grids, to complex natural phenomena such as neural connections in the brain, and interactions between genes. Networks lie at the heart of complex systems, encoding pairwise interactions between their constituent components. In this regard, complexity captures the fact that it is difficult to derive holistic system behavior from knowledge of individual components. The key premise of network science is that despite the diversity of complex systems, the behavior of their underlying networks is driven by a common set of laws. Contemporary studies focus on models and tools to understand, predict, and control the behavior of networks. However, most of these approaches are tailored to analysis of static networks, whose node and link structure does not change with time. Cognizant of the dynamic nature of most real-world networks, analysts mostly focus on static snapshots or aggregate views of studied systems, and meaningful insights cannot be guaranteed. Indeed, the recently growing trend in analysis of dynamic networks is testament to the critical need to live up to this challenge. Moreover, issues arising from temporal network evolution are exacerbated by inherent Big Data challenges. Many large-scale networks comprise billions of nodes, which are typically associated with high-dimensional, and streaming features. Furthermore, it is often impractical to observe the entire network, and analyses must be conducted on manageable or easily accessible samples of the network. Acknowledging these limitations, this dissertation leverages recent advances in statistical signal processing, optimization, and machine learning to address the aforementioned challenges. Emphasis is placed on statistical learning approaches capable of exploiting sparsity, or low rank, attributes that have been shown useful for complexity reduction. Focusing on canonical network inference tasks such as topology identification, detection of communities, and unveiling anomalous nodes, this dissertation puts forth novel statistical models, and develops efficient algorithms for dynamic network analytics. Motivated by the need for real-time processing, online renditions of the developed algorithms are advocated for handling streaming network data. For each of the research themes considered, extensive tests are conducted on simulated and real data, while pertinent comparisons with competing approaches are drawn wherever possible.
Efficient Methods for Distributed Machine Learning and Resource Management in the Internet-of-Things
(2019-06) Chen, Tianyi
Undoubtedly, this century evolves in a world of interconnected entities, where the notion of Internet-of-Things (IoT) plays a central role in the proliferation of linked devices and objects. In this context, the present dissertation deals with large-scale networked systems including IoT that consist of heterogeneous components, and can operate in unknown environments. The focus is on the theoretical and algorithmic issues at the intersection of optimization, machine learning, and networked systems. Specifically, the research objectives and innovative claims include: (T1) Scalable distributed machine learning approaches for efficient IoT implementation; and, (T2) Enhanced resource management policies for IoT by leveraging machine learning advances. Conventional machine learning approaches require centralizing the users' data on one machine or in a data center. Considering the massive amount of IoT devices, centralized learning becomes computationally intractable, and rises serious privacy concerns. The widespread consensus today is that besides data centers at the cloud, future machine learning tasks have to be performed starting from the network edge, namely mobile devices. The first contribution offers innovative distributed learning methods tailored for heterogeneous IoT setups, and with reduced communication overhead. The resultant distributed algorithm can afford provably reduced communication complexity in distributed machine learning. From learning to control, reinforcement learning will play a critical role in many complex IoT tasks such as autonomous vehicles. In this context, the thesis introduces a distributed reinforcement learning approach featured with its high communication efficiency. Optimally allocating computing and communication resources is a crucial task in IoT. The second novelty pertains to learning-aided optimization tools tailored for resource management tasks. To date, most resource management schemes are based on a pure optimization viewpoint (e.g., the dual (sub)gradient method), which incurs suboptimal performance. From the vantage point of IoT, the idea is to leverage the abundant historical data collected by devices, and formulate the resource management problem as an empirical risk minimization task --- a central topic in machine learning research. By cross-fertilizing advances of optimization and learning theory, a learn-and-adapt resource management framework is developed. An upshot of the second part is its ability to account for the feedback-limited nature of tasks in IoT. Typically, solving resource allocation problems necessitates knowledge of the models that map a resource variable to its cost or utility. Targeting scenarios where models are not available, a model-free learning scheme is developed in this thesis, along with its bandit version. These algorithms come with provable performance guarantees, even when knowledge about the underlying systems is obtained only through repeated interactions with the environment. The overarching objective of this dissertation is to wed state-of-the-art optimization and machine learning tools with the emerging IoT paradigm, in a way that they can inspire and reinforce the development of each other, with the ultimate goal of benefiting daily life.
Exploring learning during a business ethics simulation.
(2011-04) Revoir, Richard Leonard
The purpose of this study was to explore a simulation incorporating online collaborative technologies in a business ethics course to examine whether it affects student learning. A qualitative case study method of inquiry was used to develop an in-depth description and analysis of student learning during a business ethics simulation using data collected through a questionnaire, student ratings of the simulation, focus groups, and a review of videos by the researcher. The results of this study provide insight into themes that may affect students' moral sensitivity and judgment. Three key themes emerged during data analysis: 1) working in groups, 2) watching YouTube videos, and 3) experiencing less nervousness. Working in groups appeared to affect moral sensitivity because the students were exposed to more perspectives from classmates who helped them interpret the case simulation and identify ethical issues. The students reported being able to rewind and review the YouTube videos was helpful to learning. The videos also provided more perspectives and multiple approaches for reasoning which may have affected students' moral sensitivity in their effort to interpret the simulations and identify ethical issues. Students reported being less nervous while recording their YouTube video than if they had to complete the assignment in-class in front of their peers. In addition, students came to class with their YouTube video completed, they had time in class to reflect on other students' performances during class time, rather than focus on their impending performance. The findings of this study add to the literature in the area of business ethics by describing how the integration of technology for ethical simulations may affect student learning. With the three themes identified, the results of this study have implications for college instructors who are teaching business ethics courses.
Faculty Perspectives And Practices Of Social Presence In Online Post-Secondary Learning Environments
(2018-04) Smith, Julie
This study explored the almost 20-year-old Community of Inquiry (CoI) social presence construct through faculty’s perspectives and practices of their online teaching. Social presence has many CoI-identified characteristics, but overall it is the ability of a student to project their persona into the classroom. The preponderance of investigation has been on the other two CoI constructs, teaching and cognitive presences. Questions have arisen whether social presence is even necessary or achievable in online learning. This research was to provide more insight on the importance of online social presence and its characteristics in the online learning environment. The investigation invited faculty of a Midwestern university who teach solely online courses to share their perspectives on and practices supporting social presence. Methodology employed was inquiry-based, qualitative research utilizing survey and interview questionnaires. The sample consisted of 62 survey respondents and six interviewees. Data and information gathered were survey respondents’ demographics, type and sizes of courses they taught, and responses to qualitative and Likert-scaled questions, as well as interviewees’ qualitative responses. These findings were analyzed using descriptive statistics, Pearson correlations, and qualitative information review to find patterns to help answer the research questions. From the survey data, significant Pearson Correlations were present related to very small (less than 21 students) and very large classes (over 80 students). Most social presence CoI characteristics were rated at least important to extremely important by over 50% of the faculty responses. Only two characteristics rated mostly somewhat important or not important. From the survey and interview responses, patterns arose that social presence is contextually important and can be impacted by class size, instructor course design, the course level (undergraduate versus graduate), subject matter, student’s self-regulate learning, and the amount of time and resources allotted to the instructor. A few survey responses stated that social presence is not at all important. Interviewees relayed that online social presence can be just as important as it is in face-to-face courses for learning outcomes. This investigation warrants more social presence research regarding class size and level, subject matter, institutional supports, instructor course design, student self-learning abilities, and CoI construct-to-construct impacts.
The Impacts of Asynchronous Video Reflection on Perceived Learner Social Presence
(2015-12) Koivula, Matti
This dissertation examined how an asynchronous video reflection tool impacted learners’ perception of social presence and their feeling of community in an online learning environment. More than ever before learning in postsecondary education takes place online through computer mediated communication, as almost all colleges and universities offer some of their courses online (Moore & Kearsley, 2012). There are many benefits of online learning (Graham, 2006; Griffiths & Graham, 2009b; Rourke, Anderson, Garrison, & Archer, 2001), but there are problems as well. One of the problems students can have while learning online is the feeling of isolation and the lack social presence with others (Ali & Leeds, 2009; Borup, West, & Graham, 2012; Rovai, 2002). To help mediate this problem, instructors use different online technologies that encourage learners to communicate in a variety of ways, including through video and visual media. There are many video-based tools available and many are newly in development; this study examines one in particular called Flipgrid that can be used by instructors and students to create and share video-based reflections on course content. The purpose of this study is to help online instructors, instructional designers and educational app developers find new ways of enhancing or increasing social presence for their target audience by exploring the following research questions: (1) How does an asynchronous video reflection tool impact students’ perception of social presence in an online class? (2) How does seeing classmates’ video recordings influence students’ feeling of community in an online class? And (3) How does creating video recordings influence students’ feeling of community in an online class? This interpretive case study (Stake, 1995) was informed by the Community of Inquiry framework (Garrison, Anderson, & Archer, 2000) and utilized qualitative methods for data collection and inductive data analysis to understand the phenomenon of social presence and how learners experienced it while using an asynchronous video reflection tool. Data was collected from students from five separate undergraduate courses that took place fully online. Analysis of qualitative surveys, focus group, and individual interviews revealed three themes from the data: familiarization, authenticity, and distractions. Participants expressed that getting to know classmates by seeing and hearing them in an online course was important to them, and authentic videos in which students shared personal stories to support their points of views were highly valued. There were also distracting elements, like privacy concerns and the feeling of being rushed while doing recording, that negatively impacted the experience of recording and watching video reflections. Based on the findings of this study, a refined definition of social presence is proposed.
Learner characteristics as early predictor of persistence in Online courses
(2015-02) Asdi, Ahmad Kashif
The purpose of this study was to examine how learner characteristics could be used to predict whether or not a college learner would persist in the first online course and, more importantly, enroll in the next two terms. The four learner characteristics examined were learners' pre-course basic verbal score, college application score, degree level, and start date. The data were collected from 2,674 learners who were enrolled in one of the online public service and health graduate programs at a large Midwestern university. A quantitative study was conducted to investigate the research questions. The chi-square test of association, a nonparametric statistical test, was used to determine if there were any significant differences between variables of the data. The following descriptive statistics were used to describe the data: frequency distributions, means, standard deviations, and percentages. Stepwise logistic regression was used to understand whether learner persistence can be predicted based on a learner's pre-course basic verbal score, application score, degree level, and start date.The tests results revealed a statistically significant difference between learners who completed their first course and learners who dropped out of their first course with respect to pre-course basic verbal, application score, and degree level. There was no statistically significant difference between the two groups with respect to start date. The logistic regression model was found to be statistically significant (p < .0005); however, the model explained only 1.7% of the variance in learner persistence; hence, this model needs to be used with caution. Of the four independent variables, only application score (p < .0005) added significantly to the model. This study supports the idea that learners who have higher application scores are more likely to complete the first course and enroll in the next two terms.The findings of this study can contribute to the scholarly work in the field and potentially provide the base for future interventions to improve learner persistence in the first online course and enrollment in the next two terms.
Online Action Selection Methods for Multi-Agent Navigation
(2016-06) Godoy Del Campo, Julio
In multi-agent navigation, agents have to move from their start positions to their goal locations while avoiding collisions with other agents and any static element in the environment. Existing methods either compute the motion of each agent centrally or allow each agent to compute its own motion. Using a central controller limits the number of agents that can be controlled in real time, while using a local method produces motions that are optimal locally but do not account for the motions of the other agents, producing inefficient global motions when many agents move in a crowded space. This dissertation proposes a set of online action selection methods that each agent uses to dynamically adapt its behavior to the local conditions. Specifically, we propose four approaches based on learning, planning, coordination and model inference to improve the global motions of a set of agents. These approaches are highly scalable because each agent makes its own decisions on how to move. We validate the approaches experimentally, with multiple simulations in a variety of environments and with different numbers of agents. When compared to other techniques, the proposed approaches produce motions that are more efficient and make better use of the space, allowing agents to reach their destinations faster.
Online Learning Preferences: 4‐H Volunteer Survey & Focus Group Findings
(University of Minnesota Extension Center for Youth Development, 2019-04) Robideau, Kari
An online survey was distributed by email to a sample of Minnesota 4-H adult volunteers who attended one or more trainings, online and/or in-person, within 18 months. Following the survey, two focus groups were conducted through a web-based seminar to provide further insight into the survey findings. This report outlines the findings from the survey and the focus group, followed by implications for training 4-H volunteers in online settings.
A phenomenological investigation of Online learners' lived experiences of engagement
(2014-10) Pazurek-Tork, Angelica L.
This study examined the phenomenon of learner engagement as it was experienced by adult learners while learning online. Learner engagement has been suggested to be one of the most significant predictors of learning and academic achievement (National Research Council, 2004; Russell, Ainley, & Frydenberg, 2005; Skinner & Belmont, 1993), and several instructional design models have been proposed to meet the challenges associated with supporting engagement among learners in online learning environments (Kearsley, 2000; Conrad & Donaldson, 2004). However, many of these models are based on abstract conceptualizations of engagement, which vary greatly, rather than how it is actually experienced by online learners. As online learning becomes increasingly more prevalent in various adult learning and postsecondary educational contexts (The Chronicle of Higher Education, 2010), educators are prompted to consider how engagement is actually being experienced by adult learners within virtual environments, what dynamics influence it, and how their efforts might help promote and foster it. A phenomenological understanding of learners' perceptions as they experience engagement while learning in online courses holds great potential to provide new insights into online teaching and learning from an authentic, learner-centered perspective. To this end, the purpose of this study is to help adult and higher education professionals, including online instructors, facilitators, and instructional designers, understand more deeply how adult learners may experience engagement in online learning environments by addressing the following research questions: (1) What is it like to be an adult learner in online learning environments? (2) What is it like to experience engagement in online learning environments? and (3) How do various elements of learning online and dynamics of the learning environment influence adult learners' feelings of engagement?This qualitative study utilized interpretive phenomenological methodology and a post-intentional phenomenological research design (Vagle, 2010a) to investigate four adult learners' lived experiences of engagement while enrolled in a completely online, graduate-level, university course. For eight months following the conclusion of the course, qualitative methods were used to collect data from the research participants' personal narrative accounts shared through individual interviews, written lived experience descriptions (van Manen, 1990, p. 63-66), and other digital media artifacts created as part of the learning activities while the course was in progress. Iterative cycles of phenomenological data analysis using a whole-parts-whole approach captured tentative manifestations (Vagle, 2010a, p. 7) of the phenomenon of engagement as it was experienced in online learning environments and revealed in shifting and changing ways. Thematic analysis (van Manen, 1990, p. 78) was also used to identify three themes of pedagogic significance: (1) The unbounded nature of learning online may significantly impact the overall learning experience, especially how engagement is experienced; (2) Engagement may be experienced online as a form of praxis; and (3) There is a temporal nature to engagement in online learning environments, suggesting that it changes over time and space, according to the influence of various dynamics. Research findings also suggest particular dynamics that influenced the lived experience of engagement online, including learner autonomy and shared decision-making. The insights gained from this study were used to propose a flexible online engagement model that suggests research-based pedagogical design principles to help promote and foster engaging online learning experiences.
The purpose and potential of virtual high schools: a national Study of virtual high schools and their head administrators.
(2009-11) Brown, Rachel Anne
Purpose: The purpose of this study was to investigate the emerging world of virtual high schools and the people who lead them to better understand virtual schooling’s purpose and potential, particularly within the context of public education in the United States. Data collection and analysis: The mixed-methods study used three sequential phases. The first was a document analysis of the 142 virtual school Web sites listed on the NACOL Clearinghouse List (the only national list available) to identify key characteristics of the schools and programs. The second was a survey of the head administrators of all these schools (n=58, response rate = 46%), with 27 questions focusing on enrollment information, mission and purpose, curriculum and instruction, school management and leadership, and head administrators’ personal and professional characteristics. The third phase, semi-structured interviews of eight of the survey respondents, addressed exploratory questions about their work, their school, beliefs about virtual schooling, and predictions for the future. The head administrators interviewed were from the five main types of virtual schools (state, public school/district, charter, private, and university-based). Qualitative analysis was done with a blend of an immersive approach and a template analysis. Findings: In terms of basic characteristics, there appear to be some patterns emerging, particularly by virtual school type. Virtual school administrators believed that K-12 virtual schools will continue to expand and that online learning will become a mainstream component of K-12 students’ education. They believed a key purpose of virtual schools is to individualize students’ educational experiences, both in terms of increasing course options and for personalizing instruction. Those leading the publicly funded virtual schools (state, charter and district/school) believed a purpose of virtual schools is to reform the traditional education systems. Head administrators surveyed shared a variety of characteristics and described their work as similar to a traditional principal with an emphasis on instructional leadership and marketing. They were of the first generation of virtual school leaders and came to their roles as experienced educators who had a desire to innovate and to transform education.
Strategies for the Adult Learner in Non-Credit Classes: Building Engagement into Online Classes
(University of Minnesota Extension Center for Youth Development, 2011) Robideau, Kari; Vogel, Eric
This white paper contains strategies learned by the authors, academically and through experience, about what it takes to intentionally create an engaging online experience with adults in non-credit settings.
Tips for Online Learning: Using Discussion Boards to Enhance Your Online Learning
(University of Minnesota Extension Center for Youth Development, 2015) Robideau, Kari; Frendo, Molly
Cohort-based online courses often include a discussion board. Participants can interact in a discussion board by sharing what they have learned, expressing how they will apply the information, reacting to other participants’ posts, and asking questions. This white paper offers tips for using discussion boards to enhance online learning.
Web Site usability: a case study of student perceptions of educational web sites.
(2010-05) Ballard, Joyce Kimberly
As distance education has moved from traditional correspondence courses to online educational web sites, it becomes important to look at the usability or "ease of use" of instructional web sites from the student's perspective. The nonlinear, hypertext format of the Web can pose various problems for learners as they attempt to complete course-related tasks. Any difficulties that students have using this technology will compound and increase their cognitive load above and beyond learning the course content. Although many articles and books have been published about web-based learning, only limited empirical research has emerged to inform the development and design of educational course sites. This research explored what the construct of usability means for students taking online courses from the perspective of 74 students enrolled in an online and distance learning program. Six courses, matched on subject matter, were selected for study. These courses were designed and developed by two different groups, professional and nonprofessional developers. Starting with an expert heuristic evaluation of the course sites, this study used both quantitative and qualitative measures to record the experiences of students enrolled in these six courses and determine how students judge the usability of educational web sites. Based on the analysis of the study variables according to course development type, the results of this study found that Nielsen's usability heuristics (a respected evaluation tool used primarily to measure the usability of commercial web sites) can be used to evaluate instructional web sites and used to differentiate between levels of usability in the same way that usability is judged by students.
Webinar Evaluation Rubric for Extension Teaching
(University of Minnesota Extension Center for Youth Development, 2017) Matthes, K.; Robideau, K.
This is an evaluation tool that will assess the effectiveness and quality of extension staff teaching. This evaluation tool will be used by practicing webinar facilitators who want a way to evaluate their work and demonstrate teaching excellence. This rubric may be used as a reflective practice tool for the teacher, and/or as a peer review by a colleague.

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